Question

我很确定我的一般主题是正确的，但我找不到任何面孔。我的代码从c=cv2.VideoCapture(0)读取，即计算机的摄像机。然后我进行以下设置以获得面部的位置。正如你所看到的，我循环遍历不同的scaleFactors和minNeighbors，但rects总是返回空。我还尝试了opencv / data / haarcascades包中包含的四个不同haarcascade xml文件中的每一个。

任何提示？

while(1):
    ret, frame = c.read()
    rects = find_face_from_img(frame)

def detect(img, cascade):
    for scale in [float(i)/10 for i in range(11, 15)]:
        for neighbors in range(2,5):
            rects = cascade.detectMultiScale(img, scaleFactor=scale, minNeighbors=neighbors,
                                             minSize=(20, 20), flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
            print 'scale: %s, neighbors: %s, len rects: %d' % (scale, neighbors, len(rects))

def find_face_from_img(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.equalizeHist(gray)
    rects = detect(gray, cascade)

Answer 1

为了让它在我的电脑上运行，我稍微改变了你的代码。当我跑步时，我得到了结果

import cv2
import cv2.cv as cv
import getopt, sys

def detect(img, cascade):
    for scale in [float(i)/10 for i in range(11, 15)]:
        for neighbors in range(2,5):
            rects = cascade.detectMultiScale(img, scaleFactor=scale, minNeighbors=neighbors,
                                             minSize=(20, 20), flags=cv2.cv.CV_HAAR_SCALE_IMAGE)

            print 'scale: %s, neighbors: %s, len rects: %d' % (scale, neighbors, len(rects))


def find_face_from_img(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.equalizeHist(gray)
    rects = detect(gray, cascade)


if __name__ == '__main__':

    args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
    try: video_src = video_src[0]
    except: video_src = 0
    args = dict(args)


    cascade_fn = args.get('--cascade', "cascades/haarcascade_frontalface_alt.xml")
    cascade = cv2.CascadeClassifier(cascade_fn)

    c=cv2.VideoCapture(0)
    while(1):
        ret, frame = c.read()
        rects = find_face_from_img(frame)
        if 0xFF & cv2.waitKey(5) == 27:
                break

输出：

scale: 1.2, neighbors: 2, len rects: 1
scale: 1.2, neighbors: 3, len rects: 1
scale: 1.2, neighbors: 4, len rects: 1
scale: 1.3, neighbors: 2, len rects: 1
scale: 1.3, neighbors: 3, len rects: 1
scale: 1.3, neighbors: 4, len rects: 0
scale: 1.4, neighbors: 2, len rects: 1
scale: 1.4, neighbors: 3, len rects: 0
scale: 1.4, neighbors: 4, len rects: 0
scale: 1.1, neighbors: 2, len rects: 1
scale: 1.1, neighbors: 3, len rects: 1
scale: 1.1, neighbors: 4, len rects: 1
scale: 1.2, neighbors: 2, len rects: 1
scale: 1.2, neighbors: 3, len rects: 1
scale: 1.2, neighbors: 4, len rects: 1
scale: 1.3, neighbors: 2, len rects: 1

一些建议：不要选择你的minSize太低......否则会检测到类似于脸部的每个小物品。

我假设您正在浏览所有这些参数以找到最佳参数。我发现minNeighors不应该太高，否则就找不到了。

确保您的cascade xml文件已正确链接。如果找不到，它就不会出错，只会找不到面孔。

使用OpenCV detectMultiScale找到我的脸

1 个答案: